A self-localizing autonomous underwater vehicle swarm that is operable to accurately localize each individual unit within the swarm while only requiring a single node at a known location to do so. The methods described herein can localize all members of a swarm with minimal, if any, effect on the size, weight, power, and cost of a system.
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1. A computer program product including one or more non-transitory machine-readable mediums encoded with instructions that when executed by one or more processors cause a process to be carried out for localizing a swarm comprising: providing the swarm having at least four nodes into a mixed-medium environment, wherein at least three of the at least four nodes are provided into a first medium of the mixed-medium environment and at least one of the at least four nodes is provided into a second medium of the mixed-medium environment, said mixed-medium environment consisting of at least two different mediums consisting of air, water, liquid, land, or space; determining a known location for a first node of the at least four nodes; measuring a distance between each node of the at least three nodes provided into the first medium of the mixed-medium environment and each of the at least one node provided into the second medium of the mixed-medium environment, via a timing of a communications signal sent between the first node and each of the other nodes of the at least four nodes; and calculating a three dimensional position of each node via the distances between the first node and each of the other nodes of the at least four nodes and a depth component from a pressure sensor on at least one node wherein each node of the at least four nodes is divided into a group of localized or unlocalized nodes; said group of localized nodes comprising nodes that are connected to a known locus with three other nodes likewise connected to the known locus or nodes localized via line of sight with at least three already localized nodes; and said group of unlocalized nodes comprising nodes of unknown loci which are localized when a number of unique connections is at least as large as a number of unknown loci.
Robotics and distributed systems. This invention addresses the challenge of accurately determining the positions of multiple mobile entities, referred to as a swarm, operating in a complex environment composed of different mediums. The swarm consists of at least four nodes. The process involves placing the swarm into a mixed-medium environment, which includes at least two distinct mediums such as air, water, liquid, land, or space. Specifically, at least three nodes are placed in a first medium, and at least one node is placed in a second, different medium. A known location for one of the nodes is established. The system then measures the distances between nodes in the first medium and nodes in the second medium. This is achieved by timing communication signals exchanged between a designated first node and all other nodes in the swarm. Additionally, a depth component is obtained from a pressure sensor on at least one node. Using these measured distances and the depth component, the three-dimensional position of each node is calculated. The nodes are categorized into localized and unlocalized groups. Localized nodes are those connected to a known reference point with at least three other nodes also connected to that reference, or nodes that can see at least three already localized nodes. Unlocalized nodes are those whose positions are initially unknown but become localized when they have a sufficient number of unique connections, equal to or greater than the number of unknown loci.
2. The computer program product of claim 1 wherein the communications signal used in the first medium of the mixed-medium environment is an acoustic communications signal.
This invention relates to a computer program product for managing communications in a mixed-medium environment, where information is transmitted using different types of signals. The problem addressed is the need for efficient and reliable communication in environments where multiple mediums, such as acoustic and electromagnetic signals, are used simultaneously. The invention specifically focuses on systems where the first medium employs an acoustic communications signal, which is a sound-based signal used to transmit data between devices. The acoustic signal may be modulated to encode information, allowing devices to exchange data through sound waves. The system ensures compatibility and coordination between the acoustic signal and other signals in the mixed-medium environment, optimizing data transmission and reducing interference. The invention may include mechanisms for signal modulation, demodulation, synchronization, and error correction to maintain reliable communication. The acoustic signal can be used in various applications, such as underwater communication, industrial automation, or short-range wireless systems where electromagnetic signals are less effective. The invention improves communication efficiency by leveraging the strengths of acoustic signals in specific environments while integrating them with other communication mediums.
3. The computer program product of claim 1 further comprising: continuously timing the communications signal between the first node and each of the other nodes of the at least four nodes; and continuously calculating the position of each node via the distances between the first node and each of the other nodes of the at least four nodes in real-time.
This invention relates to a computer program product for real-time positioning of nodes in a network. The system involves at least four nodes, where one node acts as a reference point for determining the positions of the other nodes. The program continuously measures the communication signal between the reference node and each of the other nodes, using these signals to calculate distances between them. By analyzing these distances in real-time, the program determines and updates the positions of all nodes dynamically. This approach enables precise, continuous tracking of node locations, which is useful in applications requiring real-time spatial awareness, such as wireless sensor networks, asset tracking, or autonomous navigation. The system ensures accurate positioning by continuously recalculating distances and positions based on the latest signal data, allowing for adjustments as nodes move or environmental conditions change. The invention improves upon traditional positioning methods by providing real-time updates without requiring external infrastructure, making it suitable for decentralized or mobile networks.
4. The computer program product of claim 1 wherein the at least three of the at least four nodes is an autonomous underwater vehicle (AUV).
This invention relates to a distributed underwater communication and data processing system using autonomous underwater vehicles (AUVs) and other nodes. The system addresses challenges in underwater environments, such as limited communication range, high latency, and harsh conditions, by leveraging multiple nodes to relay data and perform distributed processing. At least three of the four nodes in the system are AUVs, which are mobile and capable of navigating underwater to establish communication links and collect data. These AUVs may work alongside other nodes, such as fixed underwater sensors or surface buoys, to form a network that enhances data transmission reliability and efficiency. The system enables real-time or near-real-time data sharing, collaborative decision-making, and adaptive routing to overcome the inherent limitations of underwater communication. The AUVs may also perform tasks such as environmental monitoring, search and rescue, or infrastructure inspection, while maintaining connectivity with other nodes to relay collected data. The use of multiple AUVs ensures redundancy and fault tolerance, improving the system's robustness in dynamic underwater environments. The invention focuses on optimizing underwater data collection, processing, and transmission through a distributed network of mobile and stationary nodes.
5. The computer program product of claim 1 further comprising: communicating the three dimensional position of each node of the at least four nodes to a remote receiver outside of the swarm.
This invention relates to a system for determining and communicating the three-dimensional positions of nodes within a swarm of autonomous devices. The swarm consists of at least four nodes, each equipped with sensors and communication capabilities. The system calculates the relative positions of these nodes using signals exchanged between them, such as radio frequency, acoustic, or optical signals, to establish distances and angles. By analyzing these measurements, the system constructs a three-dimensional spatial map of the swarm's configuration. Additionally, the system transmits the three-dimensional position data of each node to a remote receiver located outside the swarm, enabling external monitoring and control. This technology is useful in applications like drone swarms, underwater robotics, or autonomous vehicle coordination, where precise spatial awareness is critical. The system enhances situational awareness by providing real-time positional data to external systems, improving coordination and decision-making. The invention addresses challenges in distributed positioning, particularly in environments where global positioning systems (GPS) are unreliable or unavailable.
6. The computer program product of claim 1 , wherein the at least four nodes are configured to transmit electromagnetic signals from at least one of sonar, acoustic and radar.
This invention relates to a distributed sensor network system for environmental monitoring, particularly in underwater or airborne applications where traditional communication methods are challenging. The system addresses the problem of reliable data transmission and coordination among multiple nodes in harsh or obstructed environments by using a combination of sonar, acoustic, and radar signals for communication. The network consists of at least four nodes, each capable of transmitting and receiving electromagnetic signals across these modalities to ensure robust data exchange. The nodes may operate in dynamic conditions, such as underwater or in areas with significant interference, where a single communication method would be insufficient. By integrating multiple signal types, the system enhances redundancy and reliability, allowing for continuous monitoring and data collection in environments where conventional wireless or wired networks fail. The nodes may also be configured to adapt their communication protocols based on environmental conditions, optimizing signal strength and frequency to maintain connectivity. This approach improves situational awareness and data integrity in applications like underwater surveillance, marine research, or airborne tracking. The system's modular design allows for scalability, enabling additional nodes to be integrated as needed.
7. The computer program product of claim 1 , wherein the at least four nodes are configured to receive electromagnetic signals from at least one of sonar, acoustic and navigation systems.
This invention relates to a computer program product for processing electromagnetic signals in a distributed network system. The system includes at least four nodes interconnected to form a network, where each node is capable of receiving and processing electromagnetic signals. These signals originate from at least one of sonar, acoustic, or navigation systems. The nodes are configured to communicate with each other to share and analyze the received signals, enabling enhanced data processing and decision-making. The distributed architecture improves reliability and redundancy, ensuring continuous operation even if some nodes fail. The system is particularly useful in applications requiring real-time signal analysis, such as underwater surveillance, marine navigation, or environmental monitoring. By integrating signals from multiple sources, the system provides a comprehensive and accurate representation of the environment, improving situational awareness and operational efficiency. The nodes may be deployed in various configurations, including fixed or mobile setups, depending on the application requirements. The invention addresses challenges in signal processing and data fusion by leveraging a decentralized network to enhance robustness and scalability.
8. A method of localizing a swarm of nodes comprising: providing the swarm of nodes into a mixed-medium environment, wherein at least three nodes of the swarm of nodes are deployed into a first medium of the mixed-medium environment and at least three other nodes of the plurality of nodes are deployed into a second medium of the mixed-medium environment, wherein the mixed-medium environment consists of at least two different mediums consisting of air, water, liquid, land, or space; determining a known location for a first node of the plurality of nodes; measuring a distance between each node of the plurality of nodes deployed into the first medium, each other node deployed into the first medium, and the first node with the known location via a timing of a communications signal sent between each node and each other node of the plurality of nodes; measuring a distance between each node of the plurality of nodes deployed into the second medium, each other node deployed into the second medium, and the first node with the known location via the timing of the communications signal sent between each node and each other node of the plurality of nodes; and calculating a position of each node of the plurality of nodes via the distances between each node and each of the other nodes of the plurality of nodes wherein each node of the plurality nodes is divided into a group of localized or unlocalized nodes; said group of localized nodes comprising nodes that are connected to a known locus with three other nodes likewise connected to the known locus or nodes localized via line of sight with at least three already localized nodes; and said group of unlocalized nodes comprising nodes of unknown loci which are localized when a number of unique connections is at least as large as a number of unknown loci.
A method for localizing a swarm of nodes in a mixed-medium environment involves deploying at least three nodes into a first medium and at least three other nodes into a second medium, where the environment consists of at least two different mediums such as air, water, liquid, land, or space. The method begins by determining a known location for one node in the swarm. Distances between nodes within the first medium, between nodes within the second medium, and between nodes across the two mediums are measured using the timing of communication signals exchanged between them. The position of each node is then calculated based on these measured distances. The nodes are categorized into localized and unlocalized groups. Localized nodes are those connected to a known reference point with at least three other nodes or those localized via line-of-sight with at least three already localized nodes. Unlocalized nodes are those with unknown positions, which become localized when the number of unique connections is sufficient to determine their positions. This approach enables precise localization of nodes across different environmental mediums by leveraging signal timing and connectivity.
9. The method of claim 8 wherein the first node is a communications node deployed into a position at a boundary between the first and second mediums, the communications node being operable to communicate with each node of the plurality of nodes deployed into both the first and second mediums.
This invention relates to a system for deploying and managing a network of nodes across different mediums, such as air and water, to facilitate communication between nodes in both environments. The problem addressed is the challenge of maintaining reliable communication across boundaries between dissimilar mediums, where traditional networking methods may fail due to environmental differences. The system includes a plurality of nodes deployed in both a first medium (e.g., air) and a second medium (e.g., water). A first node, acting as a boundary node, is positioned at the interface between the two mediums. This boundary node is specifically designed to communicate with all other nodes in both mediums, ensuring seamless data transmission across the boundary. The boundary node may use specialized transceivers or protocols to adapt to the differing communication conditions in each medium, such as adjusting signal strength, frequency, or modulation techniques. The system may also include additional nodes deployed in each medium, which relay data to and from the boundary node. These nodes may be arranged in a mesh or hierarchical network structure to optimize coverage and redundancy. The boundary node ensures that data from nodes in one medium can be transmitted to nodes in the other medium, enabling continuous communication across the boundary. This approach is particularly useful in applications such as underwater monitoring, environmental sensing, or disaster response, where communication must span different physical environments.
10. The method of claim 9 wherein the first medium of the mixed-medium environment is an in-water environment, the second medium of the mixed-medium environment is an airborne environment, and wherein the first node is deployed to a surface of a body of water in which at least three nodes of the plurality of nodes is deployed.
This invention relates to a method for deploying and managing a network of nodes in a mixed-medium environment, specifically where the first medium is an in-water environment and the second medium is an airborne environment. The problem addressed is the challenge of maintaining reliable communication and coordination between nodes operating across different environmental media, such as water and air, particularly in scenarios where nodes are deployed on the surface of a body of water and underwater. The method involves deploying a plurality of nodes, where at least one node is positioned at the surface of a body of water and at least three nodes are submerged underwater. The surface node acts as an intermediary, facilitating communication between the underwater nodes and nodes in the airborne environment. This setup ensures seamless data transmission and coordination across the mixed-medium environment, overcoming the limitations of direct communication between underwater and airborne nodes due to differing propagation characteristics. The surface node may be equipped with transceivers capable of operating in both water and air, enabling it to relay signals between the submerged nodes and airborne nodes. The submerged nodes may be arranged in a network to enhance coverage and redundancy, ensuring robust communication even in dynamic underwater conditions. The method optimizes node placement and communication protocols to maintain connectivity and data integrity across the mixed-medium environment.
11. The method of claim 8 wherein one of the first medium is water and further comprising detecting a non-cooperative object with at least one node using at least one sensor, wherein the at least one sensor provides visual detection, sonar detection, or radar detection; and determining a location of the non-cooperative object relative to the at least one node.
This invention relates to underwater or surface-based detection systems for identifying and locating non-cooperative objects, such as those that do not actively transmit identification signals. The system uses at least one node equipped with sensors capable of visual, sonar, or radar detection to monitor a medium, such as water. The node detects the presence of a non-cooperative object and determines its location relative to the node. The detection process involves analyzing sensor data to identify the object and calculating its position using triangulation or other localization techniques. The system may be part of a larger network of nodes working together to enhance detection accuracy and coverage. This technology is useful in maritime surveillance, underwater exploration, and security applications where tracking uncooperative targets is critical. The method ensures reliable detection and positioning of objects that do not actively participate in identification processes, improving situational awareness in dynamic environments.
12. The method of claim 11 wherein determining the location of the at least one non-cooperative object further comprises: measuring a distance between the at least one non-cooperative object and at least one node of the at least four nodes having a line of sight to the at least one non-cooperative object.
This invention relates to a system for determining the location of non-cooperative objects, such as those that do not emit or reflect signals for tracking. The system uses a network of at least four nodes, each capable of communicating with the others and having a line of sight to the object. The nodes measure the distance between themselves and the non-cooperative object, using techniques such as time-of-flight or signal strength analysis. By combining these distance measurements from multiple nodes, the system calculates the precise location of the object through triangulation or trilateration. The method ensures accurate positioning even when the object does not actively participate in the tracking process. This approach is particularly useful in scenarios where traditional tracking methods, such as GPS or RFID, are not feasible due to the object's lack of cooperation or signal transmission. The system may be applied in surveillance, asset tracking, or environmental monitoring, where passive or unpowered objects need to be located without requiring onboard transmitters or reflectors. The invention improves upon existing methods by leveraging multiple distance measurements to enhance accuracy and reliability in determining the object's position.
13. The method of claim 11 wherein determining the location of the at least one non-cooperative object further comprises: measuring a distance between the at least one non-cooperative object and each node of the at least four nodes having a line of sight to the at least one non-cooperative object.
This invention relates to a system for determining the location of non-cooperative objects, such as those that do not actively transmit signals or cooperate with tracking systems. The problem addressed is the challenge of accurately locating such objects in environments where traditional tracking methods, like GPS or active beacons, are ineffective. The system uses a network of at least four nodes, each capable of communicating with the others and measuring distances to the non-cooperative object. The nodes must have a line of sight to the object to perform these measurements. By measuring the distance from each node to the object, the system can triangulate the object's position. This approach leverages geometric principles to calculate the exact coordinates of the object based on the known positions of the nodes and the measured distances. The method ensures accuracy by using multiple nodes to compensate for potential measurement errors or obstructions. The system may also incorporate additional techniques, such as signal reflection or time-of-flight analysis, to refine the distance measurements. This solution is particularly useful in applications like surveillance, asset tracking, or navigation in environments where traditional tracking methods are unavailable.
14. The method of claim 11 further comprising: communicating a position of the at least one non-cooperative object to remote receiver outside of the swarm.
The invention relates to a system for tracking and managing non-cooperative objects within a swarm of autonomous devices. The problem addressed is the difficulty in monitoring and relaying information about objects that do not actively participate in the swarm's communication network. The system includes a swarm of autonomous devices equipped with sensors and communication modules to detect and track non-cooperative objects. These objects may be passive or lack the capability to transmit their own position data. The swarm devices collaborate to determine the position of these objects using sensor data, such as radar, lidar, or optical sensors, and then process this data to estimate the object's location. The system further includes a method for sharing this positional data among the swarm devices to improve tracking accuracy and reliability. Additionally, the system can communicate the position of the non-cooperative object to a remote receiver outside the swarm, enabling external monitoring or control systems to access this information. This allows for broader situational awareness and coordination with external entities. The invention enhances the ability to track and manage objects that do not actively participate in the swarm's network, improving safety and operational efficiency in environments where such objects are present.
15. The method of claim 11 further comprising: continuously timing the communications signal between each node and each of the other nodes of the at least four nodes; continuously calculating the position of each node via the distances between each node and each of the other nodes of the at least four nodes in real-time; and tracking the location of the at least one non-cooperative object relative to at least one of the at least four nodes in real-time.
A system and method for real-time positioning and tracking of non-cooperative objects using a network of at least four nodes. The system addresses the challenge of accurately determining the location of objects that do not actively participate in positioning systems, such as drones, vehicles, or other moving targets. Each node in the network communicates with the others, continuously measuring the time of flight or signal propagation delay between them. These measurements are used to calculate the distances between nodes, which are then processed in real-time to determine the precise position of each node. The system further tracks the location of non-cooperative objects relative to at least one of the nodes by analyzing the signal reflections, interference patterns, or other indirect indicators from the object. This enables continuous monitoring of the object's movement without requiring it to transmit or respond to positioning signals. The method ensures high accuracy and reliability by leveraging the distributed nature of the node network and real-time computations. Applications include surveillance, asset tracking, and autonomous navigation in environments where traditional positioning systems are ineffective.
16. The method of claim 11 wherein the first medium of the multi-medium environment is an underwater environment and at least one node of the at least four nodes is an autonomous underwater vehicle (AUV).
This invention relates to communication and coordination in multi-medium environments, particularly underwater environments, where reliable data transmission and node coordination are challenging due to signal attenuation, latency, and environmental interference. The method involves a system with at least four nodes operating in a multi-medium environment, where at least one node is an autonomous underwater vehicle (AUV). The nodes are configured to exchange data and coordinate actions, with the AUV performing tasks such as environmental sensing, navigation, or data relay. The system may include additional nodes in different mediums (e.g., air or surface) to facilitate communication between underwater and above-water nodes. The method ensures robust data transmission by adapting communication protocols to the specific medium, such as using acoustic signals underwater and radio-frequency signals in air. The AUV may also adjust its trajectory or behavior based on data received from other nodes, enabling dynamic coordination in complex underwater missions. The system is designed for applications like underwater exploration, environmental monitoring, or search-and-rescue operations, where reliable communication and autonomous decision-making are critical.
17. The method of claim 16 wherein the at least one non-cooperative object is a threat object.
This invention relates to systems and methods for detecting and tracking non-cooperative objects, particularly threat objects, in a monitored environment. The technology addresses the challenge of identifying and monitoring objects that do not actively transmit identification signals, such as drones, missiles, or other hostile entities, which may pose security risks. The method involves using a sensor network to detect and track these objects in real-time, employing advanced signal processing and data fusion techniques to distinguish between different types of non-cooperative objects, including threat objects. The system integrates multiple sensor modalities, such as radar, optical, and acoustic sensors, to improve detection accuracy and reliability. The method further includes analyzing the detected objects' trajectories, behaviors, and other characteristics to assess their threat level and determine appropriate response actions. By continuously monitoring and updating the objects' positions and statuses, the system enables timely and effective countermeasures to mitigate potential threats. The invention enhances situational awareness and security in environments where non-cooperative, potentially hostile objects may be present.
18. The method of claim 17 further comprising: continuously timing the communications signal between each node and each of the other nodes of the at least four nodes; continuously calculating the position of each node via the distances between each node and each of the other nodes of the at least four nodes in real-time; tracking the location of the at least one non-cooperative object relative to at least one of the at least four nodes in real-time; and continuously communicating the position of the non-cooperative object to remote receiver outside of the swarm until a threat is avoided.
This invention relates to a system for real-time tracking and threat avoidance involving a swarm of nodes and non-cooperative objects. The system uses at least four nodes, each capable of communicating with the others, to continuously monitor and calculate their relative positions based on signal timing and distance measurements. The nodes form a network that dynamically tracks the location of one or more non-cooperative objects—such as drones, vehicles, or other moving entities—in real-time. The system continuously updates the position of these objects relative to the nodes and transmits this data to a remote receiver outside the swarm. This communication continues until a potential threat is detected and mitigated. The nodes may also adjust their positions or transmit signals to disrupt or avoid the threat. The system is designed for applications in surveillance, security, or autonomous navigation where real-time tracking and threat response are critical. The continuous timing of signals between nodes ensures accurate positioning, while real-time calculations allow for immediate adjustments to avoid collisions or other hazards. The remote receiver provides external monitoring and control, enhancing situational awareness and decision-making.
19. The method of claim 11 , calculating a three dimensional position of each node via the distances between each of the first node and each of the other nodes of the at least four nodes and a depth component from a pressure sensor on at least one node.
This invention relates to a method for determining the three-dimensional positions of nodes in a network, particularly in underwater or submerged environments where traditional positioning systems like GPS are ineffective. The method addresses the challenge of accurately locating nodes in three-dimensional space when direct line-of-sight or satellite-based positioning is unavailable. The method involves a network of at least four nodes, where each node is capable of measuring distances to the other nodes. These distance measurements are used to establish relative positions between the nodes in a two-dimensional plane. To determine the full three-dimensional position of each node, the method incorporates a depth component obtained from a pressure sensor on at least one node. The pressure sensor measures the water depth, which provides the vertical (depth) position of the node. By combining the two-dimensional positional data derived from inter-node distance measurements with the depth information, the system calculates the precise three-dimensional coordinates of each node in the network. This approach enables accurate underwater positioning without relying on external reference systems, making it suitable for applications such as underwater sensor networks, marine robotics, and subsea infrastructure monitoring. The use of pressure sensors ensures that depth information is continuously available, enhancing the reliability of the positioning system in dynamic underwater environments.
20. The method of claim 8 , wherein at least one of the first and second medium environment is a stratified medium and further comprising computing isochronic surfaces for a variable index of refraction when measuring the distance between each node of the plurality of nodes in the stratified medium.
This invention relates to distance measurement techniques in stratified medium environments, such as underwater or atmospheric conditions where the refractive index varies with depth or altitude. The problem addressed is the inaccuracy in distance measurements caused by refractive index variations, which distort propagation paths and lead to errors in node-to-node distance calculations in networks deployed in such environments. The method involves computing isochronic surfaces for a variable index of refraction when determining distances between nodes in a stratified medium. Isochronic surfaces represent points where a signal arrives at the same time, accounting for refractive index variations. By incorporating these surfaces, the method corrects for distortions caused by the stratified medium, improving measurement accuracy. The approach is particularly useful in applications like underwater acoustic sensing, atmospheric propagation modeling, or any system where nodes operate in environments with refractive index gradients. The method may be applied to one or both of the medium environments involved in the measurement, ensuring precise distance calculations regardless of refractive index variations. This technique enhances the reliability of distance-based localization, navigation, and communication in stratified media.
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March 31, 2020
March 29, 2022
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